Tian's app, GPTZero, basically uses ChatGPT against itself, checking whether "there's zero involvement or a lot of involvement" of the AI system in creating a given text. While many Americans were nursing hangovers on New Year's Day, 22-year-old Edward Tian was working feverishly on a new app to combat misuse of a powerful, new artificial intelligence tool called ChatGPT. Given the buzz it's created, there's a good chance you've heard about ChatGPT. It's an interactive chatbot powered by machine learning. The technology has basically devoured the entire Internet, reading the collective works of humanity and learning patterns in language that it can recreate.

We love Money Heist, too, but it's probably time for a break from Netflix. So, join us for our upcoming web events on bats' (undeserved?) Wednesday, May 27, 4 p.m. Eastern: Are Bats Really to Blame for the COVID-19 Pandemic? Tuesday, June 2, 4 p.m. Eastern: Free Speech Project: Should We Think Twice Before Limiting Political Advocacy? Earlier this month, Singapore unveiled Spot, a social distancing-enforcing robotic dog that is now "patrolling" a park.

Technology and artificial intelligence, we're told, are creating a New Economy, where algorithms and robots do all our work for us, increasing productivity like never before. Go by the evidence, though, and the reality looks far different. For decades, U.S. productivity grew by about 3 percent a year. After 1970, it slowed to 1.5 percent a year, then 1 percent. Today, that figure stands at 0.5 percent, and is likely to slump further from the shock of the coronavirus pandemic and mass lockdowns.

Artificial intelligence is here to save us from coronavirus. It spots new outbreaks, identifies people with fevers, diagnoses cases, prioritizes the patients most in need, reads the scientific literature, and is on its way to creating a cure. Alex Engler is a David M. Rubenstein Fellow at the Brookings Institution and an adjunct professor and affiliated scholar at Georgetown University's McCourt School of Public Policy. As the world confronts the outbreak of coronavirus, many have lauded AI as our omniscient secret weapon. Although corporate press releases and some media coverage sing its praises, AI will play only a marginal role in our fight against Covid-19.

With Uber and Lyft recently announcing large quarterly losses, it's clear they have to make serious changes to reach profitability and even stay in business. One potential path to survival is to replace their biggest operational expense, the human driver, with a fully autonomous fleet. Autonomous vehicles (AV) will save Uber and Lyft (and other companies) in addition to making our roads safer. According to the Association for Safe International Road Travel, globally, "Nearly 1.25 million people die in road crashes each year, on average 3,287 deaths a day." This is equivalent to wiping out the entire population of San Jose every year.

In wondering what can be done to steer civilization away from the abyss, I confess to being increasingly puzzled by the central enigma of contemporary cognitive psychology: To what degree are we consciously capable of changing our minds? I don't mean changing our minds as to who is the best NFL quarterback, but changing our convictions about major personal and social issues that should unite but invariably divide us. As a senior neurologist whose career began before CAT and MRI scans, I have come to feel that conscious reasoning, the commonly believed remedy for our social ills, is an illusion, an epiphenomenon supported by age-old mythology rather than convincing scientific evidence. If so, it's time for us to consider alternate ways of thinking about thinking that are more consistent with what little we do understand about brain function. I'm no apologist for artificial intelligence, but if we are going to solve the world's greatest problems, there are several major advantages in abandoning the notion of conscious reason in favor of seeing humans as having an AI-like "black-box" intelligence.

Last week Google released several thousand deepfake videos to help researchers build tools that use artificial intelligence to spot altered videos that could spawn political misinformation, corporate sabotage, or cyberbullying. Google's videos could be used to create technology that offers hope of catching deepfakes in much the way spam filters catch email spam. In reality, though, technology will only be part of the solution. That's because deepfakes will most likely improve faster than detection methods, and because human intelligence and expertise will be needed to identify deceptive videos for the foreseeable future. Deepfakes have captured the imagination of politicians, the media, and the public.

Last week Google released several thousand deepfake videos to help researchers build tools that use artificial intelligence to spot altered videos that could spawn political misinformation, corporate sabotage, or cyberbullying. Google's videos could be used to create technology that offers hope of catching deepfakes in much the way spam filters catch email spam. In reality, though, technology will only be part of the solution. That's because deepfakes will most likely improve faster than detection methods, and because human intelligence and expertise will be needed to identify deceptive videos for the foreseeable future. Deepfakes have captured the imagination of politicians, the media, and the public.

Tech billionaires Jack Ma and Elon Musk can't agree whether artificial intelligence is going to take over the world.

Ten years on from the financial crisis, stock markets are regularly reaching new highs and volatility levels new lows. The financial industry has enthusiastically and profitably embraced big data and computational algorithms, emboldened by the many triumphs of machine learning. However, it is imperative we question the confidence placed in the new generation of quantitative models, innovations which could, as William Dudley warned, "lead to excess and put the [financial] system at risk." Eighty years ago, John Maynard Keynes introduced the concept of irreducible uncertainty, distinguishing between events one can reasonably calculate probabilities for, such as the spin of a roulette wheel, and those which remain inherently unknown, such as war in ten years' time. Today, we face the risk that investors, traders, and regulators are failing to understand the extent to which technological progress is -- or more precisely is not -- reducing financial uncertainty.